FACE.zip_The Image

function [outputImage, transformationMap] = fcnBPDFHE(inputImage, fuzzyMembershipType, parameters) % %fcnBPDFHE performs Brightness Preserving Dynamic Fuzzy Histogram % Equalization (BPDFHE) on an Image % % OUTPUTIMAGE = fcnBPDFHE(INPUTIMAGE) performs BPDFHE on an image using % default parameter settings. Supported image classes for INPUTIMAGE % include uint8, uint16, int16, single, double. Default execution uses a % triangular membership function with support of 5. Default memberships % values are [1 2 3 4 5 4 3 2 1]. % % OUTPUTIMAGE = fcnBPDFHE(INPUTIMAGE,FUZZY_MEMBERSHIP_TYPE,PARAMETERS) % performs BPDFHE on the INPUTIMAGE using Fuzzy Memberships as defined in % FUZZY_MEMBERSHIP_TYPE % Options: % -------- % triangular - uses a triangular membership function % gaussian - uses a gaussian membership function % custom - uses the user defined membership values % PARAMETERS are to be specified accordingly for usage % Options: % -------- % Width of support if 'triangular'. Suggested is 5 for uint8 % Width of support and spread factor if 'gaussian'. Suggested is % [5,2] for uint8 % User defined membership values if 'custom'. Suggested is [1 2 3 4 5 4 3 2 1] % % [OUTPUTIMAGE, TRANSFORMATION_MAP] = fcnBPDFHE(...) returns also the % intensity transformation matrix for further usage. % % Details of the method are available in % D. Sheet, H. Garud, A. Suveer, J. Chatterjee and M. Mahadevappa, % "Brightness Preserving Dynamic Fuzzy Histogram Equalization", % IEEE Trans., Consumer Electronics, vol. 56, no. 4, pp. 2475 - 2480, % Nov. 2010. [http://dx.doi.org/10.1109/TCE.2010.5681130] % % H. Garud, D. Sheet, A. Suveer, P.K. Karri, A.K. Ray, M. Mahadevappa, % J. Chatterjee, "Brightness preserving contrast enhancement in digital % pathology", Proc. ICIIP 2011. % [http://dx.doi.org/10.1109/ICIIP.2011.6108964] % % 2009 (c) Debdoot Sheet, Indian Institute of Technology Kharagpur, India % Ver 1.0 28 January 2009 % Ver 2.0 11 December 2011 % Rev 1.0 14 December 2011 % Rev 2.0 15 December 2011 % % Example (Grayscale Images) % -------------------------- % inputImage = imread('cameraman.tif'); % outputImage = fcnBPDFHE(inputImage); % figure, subplot 131, imshow(inputImage), subplot 132, % imshow(outputImage), subplot 133, imshow(inputImage-outputImage,[]) % % Example (Color Images) % -------------------------- % rgbInputImage = imread('peppers.png'); % labInputImage = applycform(rgbInputImage,makecform('srgb2lab')); % Lbpdfhe = fcnBPDFHE(labInputImage(:,:,1)); % labOutputImage = cat(3,Lbpdfhe,labInputImage(:,:,2),labInputImage(:,:,3)); % rgbOutputImage = applycform(labOutputImage,makecform('lab2srgb')); % figure, subplot 121, imshow(rgbInputImage), subplot 122, % imshow(rgbOutputImage); % 2009 (c) Debdoot Sheet, Indian Institute of Technology Kharagpur, India % All rights reserved. % % Permission is hereby granted, to use, copy, modify, and distribute this code % (the source files) and its documentation for any purpose, provided that % the copyright notice in its entirety appear in all copies of this code, % and the original source of this code. Further Indian Institute of % Technology Kharagpur (IIT Kharagpur / IITKGP) is acknowledged in any % publication that reports research or any usage using this code. The work % is to be cited using the bibliography as % % D. Sheet, H. Garud, A. Suveer, J. Chatterjee and M. Mahadevappa, % "Brightness Preserving Dynamic Fuzzy Histogram Equalization", % IEEE Trans., Consumer Electronics, vol. 56, no. 4, pp. 2475 - 2480, % Nov. 2010. [http://dx.doi.org/10.1109/TCE.2010.5681130] % % Garud, H. Sheet, D. Suveer, A. Karri, P.K. Ray, A.K. Mahadevappa, M. % Chatterjee, J., "Brightness preserving contrast enhancement in digital % pathology", Proc. ICIIP 2011. % [http://dx.doi.org/10.1109/ICIIP.2011.6108964] % % In no circumstantial cases or events the Indian Institute of Technology % Kharagpur or the author(s) of this particular disclosure be liable to any % party for direct, indirectm special, incidental, or consequential % damages if any arising out of due usage. Indian Institute of Technology % Kharagpur and the author(s) disclaim any warranty, including but not % limited to the implied warranties of merchantability and fitness for a % particular purpose. The disclosure is provided hereunder "as in" % voluntarily for community development and the contributing parties have % no obligation to provide maintenance, support, updates, enhancements, % or modification. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Input argument support check iptcheckinput(inputImage,{'uint8','uint16','int16','single','double'}, {'nonsparse','2d'}, mfilename,'I',1); if nargin == 1 parameters = 5; membership = parameters(1)-abs(-parameters(1):parameters(1)); elseif nargin == 3 if strcmp(fuzzyMembershipType,'triangular') if ~(numel(parameters)==1) error('fcnBPDFHE supports only 1 parameter for Triangular Membership'); end membership = parameters(1)-abs(-parameters(1):parameters(1)); elseif strcmp(fuzzyMembershipType,'gaussian') if ~(numel(parameters)==2) error('fcnBPDFHE supports only 2 parameters for Gaussian Membership'); end membership = exp(-(-parameters(1):parameters(1)).^2/parameters(2)^2); elseif strcmp(fuzzyMembershipType,'custom') if numel(parameters)==0 error('fcnBPDFHE requires the membership value specification as 1-D array for Custom Membership'); end membership = parameters; else error('Unsupported membership type declaration'); end else error('Unsupported calling of fcnBPDFHE'); end imageType = class(inputImage); % Histogram creation if strcmp(class(inputImage),'uint8') [crispHistogram,grayScales] = imhist(inputImage); elseif strcmp(class(inputImage),'uint16') crispHistogram = zeros([2^16 1]); for counter = 1:numel(inputImage) crispHistogram(inputImage(counter)+1) = crispHistogram(inputImage(counter)+1) + 1; end grayScales = 0:(2^16 - 1); elseif strcmp(class(inputImage),'int16') crispHistogram = zeros([2^16 1]); for counter = 1:numel(inputImage) crispHistogram(inputImage(counter)+32769) = crispHistogram(inputImage(counter)+32769) + 1; end grayScales = -32768:32767; elseif (strcmp(class(inputImage),'double')||strcmp(class(inputImage),'single')) maxGray = max(inputImage(:)); minGray = min(inputImage(:)); inputImage = im2uint8(mat2gray(inputImage)); [crispHistogram,grayScales] = imhist(inputImage); end inputImage = double(inputImage); fuzzyHistogram = zeros(numel(crispHistogram)+numel(membership)-1,1); for counter = 1:numel(membership) fuzzyHistogram = fuzzyHistogram + membership(counter)*[zeros(counter-1,1);crispHistogram;zeros(numel(membership)-counter,1)]; end fuzzyHistogram = fuzzyHistogram(ceil(numel(membership)/2):end-floor(numel(membership)/2)); del1FuzzyHistogram = [0;(fuzzyHistogram(3:end)-fuzzyHistogram(1:end-2))/2;0]; del2FuzzyHistogram = [0;(del1FuzzyHistogram(3:end)-del1FuzzyHistogram(1:end-2))/2;0]; locationIndex = (2:numel(fuzzyHistogram)-1)'+1; maxLocAmbiguous = locationIndex(((del1FuzzyHistogram(1:end-2).*del1FuzzyHistogram(3:end))<0) & (del2FuzzyHistogram(2:end-1)<0)); counter = 1; maxLoc = 1; while counter < numel(maxLocAmbiguous) if (maxLocAmbiguous(counter)==(maxLocAmbiguous(counter+1)-1)) maxLoc = [maxLoc ; (maxLocAmbiguous(counter)*(fuzzyHistogram(maxLocAmbiguous(counter))>fuzzyHistogram(maxLocAmbiguous(counter+1)))) + (maxLocAmbiguous(counter+1)*(fuzzyHistogram(maxLocAmbiguous(counter))<=fuzzyHistogram(maxLocAmbiguous(counter+1))))]; count